Numerical simulation is widely used in industrial fields as a method of simulating a physical system by using a computer. In most cases, there is desire to model the transport processes occurring in the physical system. What is being transported is typically mass, energy, momentum, or some combination thereof. By using numerical simulation, it is possible to model and observe a physical phenomenon and to determine design parameters, without actual laboratory experiments and field tests.
Reservoir simulation or modeling is of great interest because it infers the behavior of a real hydrocarbon-bearing reservoir from the performance of a model of that reservoir. The typical objective of reservoir simulation is to understand the complex chemical, physical, and fluid flow processes occurring in the reservoir sufficiently well to predict future behavior of the reservoir to maximize hydrocarbon recovery.
Reservoir simulation often refers to the hydrodynamics of flow within a reservoir, but in a larger sense reservoir simulation can also refer to the total hydrocarbon system, which can include not only the reservoir, but also injection wells, production wells, surface flowlines, associated aquifers, and surface processing facilities.
Reservoir simulation calculations in such hydrocarbon systems are based on fluid flow through the entire hydrocarbon system being simulated. These calculations are performed with varying degrees of rigor, depending on the requirements of the particular simulation study and the capabilities of the simulation software being used.
One area of keen interest is H2S generation and transportation in a reservoir. H2S is an undesirable component that is produced along with oil, water, and gas from hydrocarbon reservoirs. Crude oil is considered “sour” when a high amount of sulfur impurities in both the hydrocarbon and reservoir.
The levels of produced H2S are affected by hydrocarbon composition and connate water chemistry of the reservoir, thermal processes related the depositional environment, biological reactions of sulfate reducing bacteria, natural scavenging reactions such as reactions between H2S and siderite (a FeCO3 mineral), and effects of field production methods, such as water injection. As reservoirs age and water injection is implemented for pressure maintenance, there is an inherent risk of the reservoir souring, mainly as a result of the downhole activity of sulfate-reducing bacteria (“SRB”) that metabolize the organic compounds in the reservoir and transfer electrons to sulfur, instead of oxygen (See FIG. 1).
Reservoir souring is very detrimental because H2S is a highly toxic and flammable gas. The lethal concentration is 800 ppm for 50% of humans exposed for 5 minutes, poisoning several different systems in the body. It forms a complex bond with iron in the mitochondrial cytochrome enzymes, thus preventing cellular respiration. Therefore, reservoir souring raises major safety concerns in field operations.
Corrosion is another detrimental effect of hydrogen sulfide. In the presence of moisture, H2S can act as a catalyst in the absorption of atomic hydrogen in steel, promoting sulfide stress cracking (“SSC”) in high strength steels, thus necessitating the deployment of chemical scavengers or corrosion inhibitors to protect the production facilities. Installation of chemical sweetening systems to meet export or refinery specifications is another complexity (and expense) caused by reservoir souring.
Hence, reservoir souring is both dangerous and can greatly increase the operational costs of oil production, especially when it is unpredicted in the field development plan. In addition, contamination of the produced hydrocarbons with H2S contamination reduces the sale value of products. Thus, robust predictions of concentrations and volumes of H2S that will be produced over the life of the field is important for new field development facilities basis of design, design of wells and material selections, asset and operating integrity assurance, HSE, export gas specification, and overall asset management.
Reservoir model for forecasting H2S production during the life of a field has been developed, for example, SourSimRL, which has been used in several studies to enable metallurgical selection and cost-effective mitigation strategies to be considered. This model is based on inputted information relating to reservoir's nutrients, and composition of injection and formation water. It is possible to simulate corrective action processes like biocide and nitrate injection. However, this model is somewhat simplistic. Further, SourSim was developed by Oilplus for a consortium of oil companies and the proprietary property is not available for update or refinement.
SPE-164068, for another example, describes a reservoir souring model used to help explain the lack of nitrate treatment effectiveness at controlling reservoir souring and H2S production from a moderately hot oilfield. The model was modified to include the direct metabolism of sulfate-reducing and nitrate-reducing bacteria by stoichiometric reactions between dissolved organic carbons (“DOC”), sulfate and nitrate. The availability of both volatile fatty acids and benzene, toluene, ethylbenzene, and xylene (“BTEX”) components as the DOC source within the reservoir was provided by partitioning these components from residual oil within the waterflood regions of the reservoir. Results indicated that the water-soluble volatile fatty acids (“VFAs”) would be consumed rapidly in the near-injector region by both SRB and nitrate reducing bacteria (“NRB”), with the H2S-biogeneration front moving into the reservoir where sulfate and DOC are able to mix and react. Oil-soluble BTEX components, however, continually partition from the oil into the water phase, even near the injector, allowing SRB activity to proceed throughout the waterflooded regions of the reservoir.
The historical trend of the calculated sour water concentration (“SWC”) is an indicator of the DOC source, with continually increasing field-wide SWC representing a strong likelihood of BTEX involvement in SRB activity. While a seemingly insignificant contribution of BTEX might not make a measurable difference in H2S production during the initial stages of a souring field's operation, significantly elevated future H2S production can result, even with nitrate treatments. Routinely analyzing produced water samples for all DOC components from the start of waterflood is important in identifying the DOC source for microbial activity.
Note, however, that this model didn't account for nitrite inhibition of SRB.
To fully understand and be able to predict reservoir souring accurately, it is important that further progress is made in obtaining relevant data on plausible microbiological and chemical routes and the rate and extent of contributing reactions. It is equally important to account for the relative solubility/partitioning data of H2S between oil/water, water/biofilm, water/gas phases in the reservoir and in process equipment.
The basis of the available models depend on a number of factors, the most important of which is the rate at which water moves through the reservoir. Other uncertainties include the degree of scavenging by reservoir rock (particularly iron minerals such as siderite), watercut, the type of water used (seawater versus produced water re-injection (“PWRI”) or waste-water injection (WWI)), producing gas oil ratio (“GOR”) and nutrient supply.
Most H2S models use ‘generic’ nutrient types to represent the various nutrients due to natural variation and uncertainties:SRBs+[C,N,P nutrients]+Sulphate ions→Sulphide→H2S
Generally, the more nutrients and sulphate ions present in injected water, the greater the amount of H2S generated by SRBs. As formation and injection waters can contain volatile fatty acids (VFAs), ammonium ions, amine and phosphorus compounds (e.g. production chemicals), together with substances such as natural surfactants from produced hydrocarbons, produced water can be much richer in nutrients than injected seawater. This means that the souring potential associated with produced water re-injection (PWRI) can be much higher than for seawater injection (by up to a factor of 2-3).
As H2S moves through the reservoir, it can interact with the mineralogy, particularly the iron minerals. Sulphide ions react with iron ions dissolving from iron minerals to form iron sulphide solids. This type of reaction causes natural scavenging of H2S generated by SRB:Sulphide ions+Iron ions→Iron Sulphide precipitates
The amount of H2S produced by a well going sour is related to the amount of water produced multiplied by a sour water concentration (usually expressed as ppm w/w). Most of the H2S is transported through the reservoir in injected water. This sour water concentration can be converted into a calculated gas phase H2S concentration by partitioning the H2S between the gas, oil and water at surface (or a maximum value can be obtained by assuming all of this H2S flashes into the gas phase):Sour Water Concentration=Mass of H2S Produced/Mass of Water Produced
In most cases, it is impossible to quantify the effect of the uncertainties on the overall H2S profiles due to the number of factors involved. Some of these factors are listed below:                Reservoir Heterogeneity and Breakthrough Times: The presence of high permeability streaks or fractures may increase the rate of souring by channeling water through a limited volume of rock to the producers.        Interactions with and Distribution of Mineralogy: The variability of iron mineral distribution and its interaction with injection water will determine how much natural scavenging actually occurs in practice. Other clays and minerals may also have some impact on local pH conditions and interaction with iron species. It is very difficult to quantify precisely how much scavenging is likely to occur in practice, as it is also influenced by kinetics of the dissolution/precipitation/ion exchange reactions taking place.        Surface Partitioning: The influence of kinetics, fluid composition, temperature and pressure on H2S partitioning between gas, oil, water and biofilm are not very well known. Estimates from thermodynamic calculations and field experience elsewhere tend to suggest the range of values used in the summary tables will apply in practice. Sensitivity to the actual value of the partition coefficients may be up to a factor of 3 in terms of gas phase H2S concentrations.        Effect of Reservoir Temperature: The reservoir temperature may create a smaller region around the injection wells in which the SRB can survive, although most H2S generation is thought to occur close to the injection wellbore. The actual temperature of the injection water may have an impact on the rate of conversion of sulphate to sulphide. The variety of bacterial populations (mesophiles, thermophiles, hyperthermophiles, SRBs, NRBs, etc.) means that some species may survive even at very high temperatures, but growth rates may vary and this can influence model accuracy.        Nutrient Input: The precise concentration of nutrients being injected into the reservoir and their effects on population growth of SRB (and other bacteria) are difficult to assess. Much of the modeling has been derived from history-matching of field situations based on known or estimated information from the field or laboratory.        Future Reservoir Management: Any differences in production/injection rates could have an impact on the overall H2S profile (up or down). For example, prolonged production at higher watercuts than those assumed in the profiles could increase H2S concentrations. Water shut-off could immediately reduce H2S concentrations in a well by over 50% by reducing the partitioning effect at lower watercut and by shutting off sour water. Delay in water breakthrough times by reducing rates or increasing injector-producer distances could also be potential souring mitigation techniques.        
There remain many challenges with developing robust models for predicting the souring of a reservoir. H2S concentrations and volumes predictions are complicated by the differing time and spatial scales of the processes that contribute to its production. For example, scavenging reactions are mainly affected by the pore scale, biological processes at the core scale, but the water injection scheme is determined on the field scale, and thermal processes are affected at the reservoir scale. Also the contributing mechanisms have varying degrees of sensitivities to the different physics, such as fluid dynamics, biochemistry, thermodynamics, and heat transfer. This leads to a competition between accurate and reliable prediction of H2S levels, efficient computation for a long forecast horizon, and ease-of-use and adaptability of a prediction tool for different field development configurations. These factors are hard to incorporate into a prediction model.
Accordingly, it would be advantageous to provide a means for modeling and predicting H2S concentrations and volumes on a multiscale level to account for the different mechanisms affecting H2S generation and transportation. Ideally, this method will take into account the topology of the reservoir, the chemistry and physics involved with H2S generation, and the various H2S generation mechanisms. Ideally, effects of the H2S concentration on e.g. process equipment should also be included to fully understand the economical outlook for a particular model. Thus, there exists a need in the art for more inclusive models that facilitate more accurate prediction of reservoir souring so that the appropriate preventative and protective measures can be in place.